%0 Journal Article
%T Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples
%A Fathi Elloumi
%A Zhiyuan Hu
%A Yan Li
%A Joel S Parker
%A Margaret L Gulley
%A Keith D Amos
%A Melissa A Troester
%J BMC Medical Genomics
%D 2011
%I BioMed Central
%R 10.1186/1755-8794-4-54
%X To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors.Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability.Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.Breast cancer is well-recognized as a heterogeneous disease and great progress has been made in the past decade in classifying tumors for prognosis and prediction [1-8]. Two different assays are clinically and commercially available for genomic characterization of tumors: the 21-gene OncotypeDx assay (Genome Health Inc, Redwood City, CA) for estrogen receptor (ER)-positive, early stage breast cancer [6,7] and the 70-gene Mammaprint (Agendia, Huntington Beach, CA) assay [4,5] for ER-positive and ER-negative early-stage, node-negative breast cancers. A 50-gene subtype predictor, the P
%K biomarker validation
%K genomic assays
%K breast cancer
%K normal tissue
%K bias
%U http://www.biomedcentral.com/1755-8794/4/54